节点文献
网络游戏者脑疲劳的耳穴信号小波熵特征提取
Otopoint-Signal-Based Wavelet Entropy Feature Extraction For Online Game Brain Fatigue
【摘要】 利用近红外额耳穴超低频信号的小波熵特征,实验研究大学生打反恐精英(Counter-Strike)游戏过程中的脑额区疲劳,依据1是网络成瘾的脑fMRI额叶激活增加证据,依据2是基于小波熵表征动物脑片兴奋性突触后电位的有效性。3名硕士生(平均年龄24岁)的一致实验结果是小波熵增特征:①平静态数值较低且平稳;②游戏态在90 min(均值)出现疲劳正峰。本工作为研究网络游戏者的脑疲劳提供了基础数据。
【Abstract】 In order to monitor college students’ brain-fatigues during playing online games named Counter-Strike,their near infrared otopoint signals’ super-slow frequency wavelet entropy feature is studied.There are two methodology evidences for above experiment design:① Internet addiction will excite prefrontal cortex based on reported fMRI scanning;② Wavelet entropy can be applied for featuring excitatory postsynaptic potentials from reported rat hippocampus CA1 pyramidal neurons in vitro.The 3 masters(average age of 24) students’ results show consistent wavelet entropy enhancement features in details ① low and flat values for quiet state,② high peak shows after playing game average 90 min while appearing fatigue.This work may provide basic data for researching online player brain fatigue.
【Key words】 online game; brain fatigue; prefrontal cortex otopoint; super-slow frequency; wavelet entropy;
- 【文献出处】 测控技术 ,Measurement & Control Technology , 编辑部邮箱 ,2009年08期
- 【分类号】R318.0
- 【被引频次】2
- 【下载频次】187